Effect of beam divergence angle and waterbodies on 16 QAM signal transmission in underwater communication
Bibliographic record
Abstract
Abstract Spectrally efficient 16 QAM system for underwater communication using commercial high-power LEDs is proposed in this letter. The transmitted beam divergence (BD) angle and the effect of 10 different types of waters are investigated to enable reliable communication. The results show that a BD angle of 0.029° is needed to achieve a maximum transmission distance of 6.9 m and 4.9 m when using Osram and Luminus LEDs, respectively. The effect of transmitted data rate on distance for the optimized BD angle show that at data rate of 0.5 Gbps Osram LED supported 6.6 m link distance, which reduced to 3.7 m for the Luminus LED in pure water. The proposed system is evaluated for 10 different types of waters at fixed data rate of 0.5 Gbps while using Luminus LED. The results show that waters with lower attenuation, such as Pure Water (PW), Jerlov I, Jerlov IA, and Clear Ocean (CL), enabled longer transmission distances of 3.7 m, 3.7 m, 3.6 m, and 3.4 m, respectively. Conversely, higher attenuation in Harbor I, Jerlov III, and Harbor II waters achieved shorter distances of 2.1 m, 1.6 m, and 1.5 m, respectively. The % Error Vector Magnitude (% EVM), Symbol Error Rate (SER), and Bit Error Rate (BER) metrics are used to evaluate the proposed system performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".